Dermatology

Optimizing time prediction and error classification in early melanoma detection using a hybrid RCNN-LSTM model.

Skin cancer is a terrifying disorder that affects all individuals. Due to the significant increase in the rate of melanoma skin cancer, early detection of skin cancer is now more critical than ever before. Malignant melanoma is one of the most serious forms of skin cancer, and it is caused by abnormal melanocyte cell growth. In recent years, skin cancer predictive categorization has become more ac...

Explainable ensemble learning method for OCT detection with transfer learning.

The accuracy and interpretability of artificial intelligence (AI) are crucial for the advancement of optical coherence tomography (OCT) image detection, as it can greatly reduce the manual labor required by clinicians. By prioritizing these aspects during development and application, we can make significant progress towards streamlining the clinical workflow. In this paper, we propose an explainab...

Malignancy diagnosis of liver lesion in contrast enhanced ultrasound using an end-to-end method based on deep learning.

BACKGROUND: Contrast-enhanced ultrasound (CEUS) is considered as an efficient tool for focal liver lesion characterization, given it allows real-time ...

An Analysis of Loss Functions for Heavily Imbalanced Lesion Segmentation.

Heavily imbalanced datasets are common in lesion segmentation. Specifically, the lesions usually comprise less than 5% of the whole image volume when ...

Exploring the Low-Dose Limit for Focal Hepatic Lesion Detection with a Deep Learning-Based CT Reconstruction Algorithm: A Simulation Study on Patient Images.

This study aims to investigate the maximum achievable dose reduction for applying a new deep learning-based reconstruction algorithm, namely the artif...

Tree-Based Machine Learning to Identify Predictors of Psoriasis Incidence at the Neighborhood Level: A Populational Study from Quebec, Canada.

BACKGROUND: Psoriasis is a major global health burden affecting ~ 60 million people worldwide. Existing studies on psoriasis focused on individual-lev...

Enhancing gadoxetic acid-enhanced liver MRI: a synergistic approach with deep learning CAIPIRINHA-VIBE and optimized fat suppression techniques.

OBJECTIVE: To investigate whether a deep learning (DL) controlled aliasing in parallel imaging results in higher acceleration (CAIPIRINHA)-volumetric ...

Enhancing skin lesion classification with advanced deep learning ensemble models: a path towards accurate medical diagnostics.

Skin cancer, including the highly lethal malignant melanoma, poses a significant global health challenge with a rising incidence rate. Early detection...

Automatic thoracic aorta calcium quantification using deep learning in non-contrast ECG-gated CT images.

Thoracic aorta calcium (TAC) can be assessed from cardiac computed tomography (CT) studies to improve cardiovascular risk prediction. The aim of this ...

MRI-Based Machine Learning Radiomics for Preoperative Assessment of Human Epidermal Growth Factor Receptor 2 Status in Urothelial Bladder Carcinoma.

BACKGROUND: The human epidermal growth factor receptor 2 (HER2) has recently emerged as hotspot in targeted therapy for urothelial bladder cancer (UBC...

Machine Learning Applications in Psoriasis Treatment: A Systematic Review.

Artificial intelligence in dermatology: advancements and challenges in skin of color.

Artificial intelligence (AI) uses algorithms and large language models in computers to simulate human-like problem-solving and decision-making. AI pro...

Applications of Machine Learning on Alopecia Areata: A Systematic Review.

Echoes of images: multi-loss network for image retrieval in vision transformers.

This paper introduces a novel approach to enhance content-based image retrieval, validated on two benchmark datasets: ISIC-2017 and ISIC-2018. These d...

Combining artificial intelligence and human expertise for more accurate dermoscopic melanoma diagnosis: A 2-session retrospective reader study.

Minimum labelling requirements for dermatology artificial intelligence-based Software as Medical Device (SaMD): A consensus statement.

BACKGROUND/OBJECTIVES: Artificial intelligence (AI) holds remarkable potential to improve care delivery in dermatology. End users (health professional...

Lesion segmentation using 3D scan and deep learning for the evaluation of facial portwine stain birthmarks.

BACKGROUND: Portwine stain (PWS) birthmarks are congenital vascular malformations. The quantification of PWS area is an important step in lesion class...

Deep Learning Combined with Radiologist's Intervention Achieves Accurate Segmentation of Hepatocellular Carcinoma in Dual-Phase Magnetic Resonance Images.

PURPOSE: Segmentation of hepatocellular carcinoma (HCC) is crucial; however, manual segmentation is subjective and time-consuming. Accurate and automa...

Patient and dermatologists' perspectives on augmented intelligence for melanoma screening: A prospective study.

BACKGROUND: Artificial intelligence (AI) shows promising potential to enhance human decision-making as synergistic augmented intelligence (AuI), but r...

Residual facial erythema in atopic dermatitis patients treated with dupilumab stratified by machine learning.

BACKGROUND: Persistent facial erythema represents a significant complication in atopic dermatitis (AD) patients undergoing treatment with dupilumab. S...